Abstract
Several observational studies have indicated the potential associations among calcium, vitamin D (Vit-D), and irritable bowel syndrome (IBS). However, the causal relationship deduced from these studies is subject to residual confounding factors and reverse causation. Therefore, we aimed to explore the bidirectional causal effects among serum calcium, Vit-D, PTH, and IBS at the genetic level by a two-sample Mendelian randomization (MR) analysis of the datasets from IEU OpenGWAS database. Sensitivity analyses were performed to evaluate the robustness. The estimates were presented as odds ratios (ORs) with their 95% confidence intervals (CIs). The results of the inverse variance weighted method did not reveal any causal relationship between the genetically predisposed calcium (OR = 0.92, 95% CI: 0.80–1.06, p = 0.25) and Vit-D (OR = 0.99, 95% CI: 0.83–1.19, p = 0.94) level and the risk of IBS. The bidirectional analysis demonstrated that genetic predisposition to IBS was associated with a decreased level of PTH (beta: −0.19, 95%CI: −0.34 to −0.04, p = 0.01). In conclusion, the present study indicates no causal relationship between the serum calcium and Vit-D concentrations and the risk of IBS. The potential mechanisms via which IBS affects serum PTH need to be further investigated.
Keywords: causal effects, irritable bowel syndrome, Mendelian randomization, calcium, vitamin D, parathyroid hormone
1. Introduction
Irritable bowel syndrome (IBS) is one of the most common gastrointestinal diseases, and affects approximately 5–10% of the global population, which exerts an immense impact on the patient’s quality of life, society, and economy [1]. The most complained symptoms include abdominal pain/discomfort and diarrhea/constipation. The pathogenesis of IBS is complex and recent studies bring the consensus that IBS mainly results from the disorder of gut–brain interactions [2]. Furthermore, epidemiological studies suggest that genetics, diet, gut microbiota dysbiosis, gut infection, and psychological factors are all risk factors for IBS, which can exert effects on IBS via disrupting the bidirectional interactions of the gut–brain axis [3,4]. Considering these factors, the common therapeutics for IBS include dietary exclusion, probiotics/fecal microbiota transplant, antibiotics, psychotropic medications, and symptom-relieving drugs (e.g., antispasmodics, antidiarrheal agents, and laxative) [5]. However, all the treatments have limited therapeutic effectiveness. Therefore, there is still an unmet need for improved understanding of the pathophysiological mechanisms of IBS to develop more effective therapeutic approaches.
Recent studies demonstrate that the diet and micronutrients play a vital role in the pathophysiology of IBS, and over 80% of IBS patients report food triggers for their complaints, such as dairy products, gluten, alcohol, and fried foods [6,7]. Noteworthily, dietary fibers are related to the onset of IBS symptoms, as they can exert effects on nutrients bioavailability, gut motility, stool pattern, and the gut microbiota [8]. Specifically, the insoluble fibers, which are poorly absorbed in the gut, can provoke and exacerbate the symptoms of IBS patients, while the soluble fibers can improve stool pattern [9,10]. Furthermore, FODMAPs (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols), which are rich in some vegetables, fruits, dairy products, and legumes, are also associated with the development and severity of symptoms in specific IBS subgroup via their fermentative and osmotic effects on the gut [1,11]. These findings provide some promising dietary therapies including dietary exclusion and dietary supplementation. For example, the increased intake of soluble fibers and reduced intake of insoluble fibers are suggested for IBS subjects [8]. Moreover, a low-FODMAP diet is a recommended therapy for IBS patients by the American College of Gastroenterology. Notably, several epidemiological studies have reported the deficiency of vitamin D (Vit-D) and calcium in IBS patients [7], which indicates that Vit-D and calcium would serve as promising targets for potential dietary therapies.
Calcium homeostasis, which plays a vital role in various cellular and biological processes, is mainly regulated by concerted action of the calciotropic hormones, such as Vit-D and parathyroid hormone (PTH) [12]. Studies indicate that supplementation of Vit-D and calcium might help improve the symptoms of IBS patients [13]. However, randomized controlled trials on the effects of Vit-D and calcium supplementation for IBS patients yielded contradictory results [14,15,16]. Additionally, the causal relationship among Vit-D, calcium, and the risk of IBS needs to be illustrated considering the potential unmeasured confounders or reverse causality in previous observational studies.
Based on Mendel’s law of inheritance, Mendelian randomization (MR) analysis can use genetic variants, namely single-nucleotide polymorphisms (SNPs), as instrumental variables (IVs) to estimate the causal effects of the predefined exposure on outcome [17]. Since genetic variants are randomly allocated at conception and remain stable after birth, MR is less susceptible to confounding factors and reverse causation, thus simulating the randomized controlled trials in the clinic. With the existing genome-wide association study (GWAS) databank, our study is dedicated to probing the causal association between Vit-D, calcium, PTH, and IBS via a bidirectional two-sample MR study.
2. Materials and Methods
2.1. Study Design
To investigate the causality between exposures and disease, we conducted two-sample MR analysis that used genetic variants as instrumental variables to explore the causal effects of risk factors on outcomes. Compared with observational studies, MR can avoid reverse causation and reduce confounding factors. The graphical flow of the experimental design is shown in Figure 1.
Figure 1.
(Left): a schematic diagram showing three assumptions of MR; (Right): overview of the exposures and outcomes in our MR analysis. VitD, 25-Hydroxyvitamin D; Ca, calcium; PTH, parathyroid hormone; IBS, irritable bowel syndrome.
The validity of MR analysis relies on three assumptions: (1) there is strong association between the IVs and the exposure; (2) each IV is not associated with confounding variables; (3) each IV is only associated with the outcome through the exposure; there are no alternative pathways for the association.
2.2. Data Sources and Study Population
The data of our study were obtained from the IEU OpenGWAS database (https://gwas.mrcieu.ac.uk/, accessed on 10 October 2022), a database of 244,879,032,980 genetic associations from 42,334 GWAS summary datasets, for query or download.
The datasets utilized in our study are shown in Table 1. For the dataset of Vit-D, summary statistics of serum 25-hydroxyvitamin D levels were from a GWAS of the EBI database with a sample size of 496,946 (ebi-a-GCST90000618) [18]. For the dataset of calcium, we used summary statistics from a GWAS of UK Biobank from Neale lab with a sample size of 315,153 (ukb-d-30680_irnt). For the dataset of PTH, the complete GWAS summary data on protein levels as described by Sun et al. (2018) was used (prot-a-2431) [19], and the sample size was 3301. For the dataset of IBS, summary statistics from FinnGen biobank analysis including 4605 patients of IBS and 182,423 controls were used (finn-b-K11_IBS) [20]. All cases were defined by the code M13 in the International Classification of Diseases—Tenth Revision (ICD-10).
Table 1.
The information of datasets used in our study.
| Traits | GWAS ID | Author | PMID | Ancestor | Sample Size |
|---|---|---|---|---|---|
| VitD | ebi-a-GCST90000618 | Revez et al. | 32242144 | European | 496,946 |
| Ca | ukb-d-30680_irnt | Neale lab | NA | European | 315,153 |
| PTH | prot-a-2431 | Sun et al. | 29875488 | European | 3301 |
| IBS | finn-b-K11_IBS | NA | NA | European | 187,028 |
Abbreviations: VitD, 25-hydroxyvitamin D; Ca, calcium; PTH, parathyroid hormone; IBS, irritable bowel syndrome.
All the above data samples were of European ethnicity. In all original studies, ethical approval and consent to participate were obtained.
2.3. Selection of Instrumental Variables
Firstly, the summary-level data above for Vit-D and calcium were screened by the genome-wide significance (p < 5 × 10−8) to select the SNPs genetically associated with the traits. To avoid inaccurate results due to too few SNPs, the significance threshold of PTH data was relaxed to 5 × 10−6. Secondly, we utilized the linkage disequilibrium clumping to exclude some undesirable SNPs (r2 > 0.001). Thirdly, we harmonized the respective exposure and outcome datasets using effect allele frequencies, while removing palindromic SNPs with intermediate allele frequencies. Lastly, according to the third assumption of MR that genetic variation cannot be associated with any possible confounding factor, we used PhenoScanner V2 [21] (a database of human genotype–phenotype associations) to search the SNPs and exclude those associated (p < 1 × 10−5) with confounding factors such as drinking [22], smoking [23], depression, and anxiety [24].
The IV exposure strength of genetic instruments was assessed from the F statistic using an approximation. If F > 10, there is sufficient strength to avoid a problem of weak instrument bias in the two-sample model. The F statistics were computed by the admittedly reliable formula F = R2 (N − 2)/(1 − R2). R2 and N refer to the cumulative explained variance of selected SNPs and sample size separately [25]. R2 was calculated using the formula R2 = 2 × MAF × (1 − MAF) × Beta2 [26].
2.4. Statistical Analyses
Multiple approaches were used in our study. We utilized the method of inverse variance weighted (IVW) as the primary analysis for its efficiency to estimate the causal effect. The weighted median was used as auxiliary method when the heterogeneity was significant, and the MR-Egger regression method was used to assess the pleiotropy by intercept test. According to the assumption of MR analysis, the instrumental variable must be only associated with the outcome through the risk factor; thus, if there are other pathways via which the outcome is influenced by genetic variants, bias will occur, and the horizontal pleiotropy may increase the false positive rate. Therefore, the pleiotropy should be evaluated using the method of MR-Egger and MR-PRESSO. The former can evaluate the potential pleiotropy in the IVW model, and the latter is used for testing horizontal pleiotropy via identifying and removing outlying instrumental variables (NbDistribution = 3000, SignifThreshold = 0.05). The leave-one-out sensitivity analysis was performed to evaluate the robustness of the study findings. The estimates were presented as odds ratios (ORs) with their 95% confidence intervals (CIs) per one standard deviation (SD) increase in the exposures. The statistical analyses above were performed in R 4.1.3 with R package of “TwoSampleMR” (version 0.5.6) and “MRPRESSO”.
3. Results
3.1. Instrumental Variables
In the analysis investigating the effect of Vit-D and calcium on IBS risk, 110 and 186 SNPs were screened, respectively, as potential instrumental variables (p < 5 × 10−8). As for PTH, 15 SNPs were screened for instrumental variables (p < 5 × 10−6). After linkage disequilibrium clumping and the removal of palindromic SNPs and confounders, 102, 176, and 14 SNPs could be used in the analyses as the instrumental variables of Vit-D, calcium, and PTH, respectively. The F statistics demonstrated that there was no bias due to weak instruments (F > 10, Table A1, Table A2, Table A3 and Table A4).
3.2. Main Analyses and Sensitivity Analyses
As shown in Figure 2, genetically predicted risk of IBS was not associated with the levels of vitamin D (p = 0.938, OR = 0.99, 95% CI: 0.83–1.19), calcium (p = 0.248, OR = 0.92, 95% CI: 0.80–1.06), and parathyroid hormone (p = 0.427, OR = 1.04, 95% CI: 0.94–1.15) using the IVW method. As shown in Table 2, Cochran’s Q statistics demonstrated no heterogeneity based on genetically predicted SNPs of Vit-D, calcium, and PTH (p > 0.05). The MR Egger intercept test showed no evidence of directional pleiotropy (p > 0.05). The results of the leave-one-out method demonstrated that the removal of SNP did not fundamentally affect the results, which indicated that the results were actually robust.
Figure 2.
The result of MR analysis investigating the causality between IBS and VitD, Ca, and PTH using multiple approaches. VitD, 25-hydroxyvitamin D; Ca, calcium; PTH, parathyroid hormone; IBS, irritable bowel syndrome; OR, odds ratio; 95% CI, 95% confidence interval.
Table 2.
The result of sensitivity analyses of MR.
| Exposure-Outcome | MR-PRESSO | IVW Estimates | MR-Egger Pleiotropy Test | ||
|---|---|---|---|---|---|
| Global p-Value | Cochran’s Q | p-Value | MR-Egger Intercept | p-Value | |
| VitD-IBS | 0.384 | 102.68 | 0.435 | −0.001 | 0.886 |
| Ca-IBS | 0.670 | 166.66 | 0.662 | −0.003 | 0.417 |
| PTH-IBS | 0.555 | 12.79 | 0.464 | 0.002 | 0.949 |
| IBS-VitD | 0.645 | 5.329 | 0.620 | −0.002 | 0.452 |
| IBS-Ca | 0.617 | 6.515 | 0.687 | 0.002 | 0.361 |
| IBS-PTH | 0.480 | 8.100 | 0.424 | −0.009 | 0.732 |
Abbreviations: VitD, 25-hydroxyvitamin D; Ca, calcium; PTH, parathyroid hormone; IBS, irritable bowel syndrome.
As shown in Figure 3, genetically predicted levels of PTH were associated with the risk of IBS (p = 0.012, Beta = −0.188) while IBS was not the risk factor of Vit-D (p = 0.898, Beta = −0.001) and calcium (p = 0.432, Beta = −0.006) using the IVW method. As shown in Table 2, Cochran’s Q statistics demonstrated no heterogeneity based on genetically predicted SNPs of Vit-D, calcium, and PTH (p > 0.05). The MR Egger intercept test showed no evidence of directional pleiotropy (p > 0.05). The results of the leave-one-out method demonstrated that the removal of SNP did not fundamentally affect the results, which indicated that the results were actually robust.
Figure 3.
The result of MR analysis investigating the causality between VitD, Ca, and PTH and IBS using multiple approaches. VitD, 25-hydroxyvitamin D; Ca, calcium; PTH, parathyroid hormone; IBS, irritable bowel syndrome; 95% CI, 95% confidence interval.
4. Discussion
To the best of our knowledge, this is the first two-sample MR study to generally clarify the causal relationship among calcium, Vit-D, PTH, and IBS. Despite employing the latest large sample size and strong instruments, our MR results did not indicate the significantly causal associations of genetically predicted calcium, Vit-D, and PTH with the risk of IBS.
Researchers have been devoted to exploring the role of micronutrients in the pathogenesis and treatment of IBS [27,28]. A systematic review including 12 interventional and 14 observational studies showed that IBS patients generally had lower levels of Vit-D, vitamin B2, calcium, and iron compared with control subjects. Meanwhile, studies also found that exclusion diets were associated with deficiencies of the aforementioned micronutrients [7]. As the major circulating form of Vit-D, 25-hydroxyvitamin D is used as indicator of Vit-D status. 25-Hydroxyvitamin D is critical to regulate calcium metabolism and a series of pathological and physiological processes in intestinal homeostasis [29]. The various effects of Vit-D supplementation on IBS patients were reported in several randomized controlled trials and systematic reviews. Jalili et al. conducted a randomized, double-blind, placebo-controlled clinical trial to assess the impact of Vit-D supplementation on symptoms severity and quality of life (QOL) in IBS patients and found that, compared to the placebo group, Vit-D therapy could markedly improve the symptoms and QOL of IBS patients [14]. Similarly, a systematic review and meta-analysis including four randomized, placebo-controlled trials showed that Vit-D supplementation was remarkably superior to placebo in improving the symptom severity (WMD: −84.21, 95% CI: −111.38 to −57.05, I2 = 73.2%; WMD: −28.29, 95% CI: −49.95 to −6.62, I2 = 46.6%, respectively) and QOL (WMD: 14.98, 95% CI: 12.06 to 17.90, I2 = 0.0%; WMD: 6.55, 95% CI: −2.23 to 15.33, I2 = 82.7%, respectively) of IBS patients [30]. However, the other randomized, double-blind, placebo-controlled study by Williams et al. demonstrated that there were no improvements in the IBS symptom severity and QOL between the trial (Vit-D supplementation) and placebo groups [15]. Moreover, a systematic review and meta-analysis based on six randomized controlled trials including 616 participants indicated that Vit-D supplementation led to no significant improvements in symptom severity and QOL of IBS subjects in contrast to placebo [31]. Considering that Vit-D contributes to the regulation of the gut microbiome, immune system, inflammatory processes, and the intestinal mucosal barrier, the present interventional trials on IBS mainly focused on Vit-D supplementation. Few studies evaluated the effects of calcium supplementation on IBS symptom severity and QOL. In contrast to studies that reported the relationship among Vit-D, calcium, and IBS, our study suggested no causal association among Vit-D, calcium, and IBS. The contradictory findings might be explained by several factors: trial participants with different ages, races, sexes, and vitamin D statuses, sample size, intervention duration, intervention diet, and placebo effects.
In addition, our bidirectional two-sample MR analysis identified that IBS was associated with a lower level of PTH, although there was no causal effect of PTH on IBS. The main function of PTH is to increase the concentration of serum calcium and decrease the concentration of serum phosphorus by impacting its primary target organs of bone and kidney, so as to regulate the homeostasis of calcium and phosphorus in vivo. It was noteworthy that recent studies suggested an increased risk of osteoporosis and osteoporotic fracture for IBS patients. A systematic review and meta-analysis including four cohorts and one cross-sectional study with 526,633 participants indicated that IBS patients had a remarkably higher risk of osteoporosis than the non-IBS subjects (pooled RR: 1.95, 95%CI: 1.04–3.64, I2 = 100%) [32]. Moreover, even though not statistically significant, IBS subjects had an increased risk of osteoporotic fracture (pooled RR: 1.58, 95%CI: 0.95–2.62, I2 = 99%). The possible mechanisms for the association between IBS and osteoporosis comprise chronic inflammation, abnormal activation of the hypothalamic–pituitary–adrenal (HPA) axis, smoking, and malnutrition. When suffering from osteoporosis, the secretion of PTH was reduced to inhibit the activity of osteoclasts, thus impeding the progression of osteoporosis, which might be the plausible explanation for the relationship between IBS and reduced level of PTH.
To our knowledge, this is the first study to elucidate the causal correlation among calcium, Vit-D, PTH, and IBS from the perspective of genetic variants using a bidirectional two-sample MR approach. This method could greatly circumvent the possible impacts of reverse causation and residual confounding factors, such as incomplete adjustment for confounders, the absence of high-quality evidence, and relatively small sample sizes of trials. Additionally, we performed several sensitivity analyses to strengthen the robustness of our results.
However, there are some limitations associated with this study. Firstly, the study mainly analyzed the European participants enrolled in the GWAS biobank; hence, the results could not precisely reflect the fact of patients from other regions and races. Secondly, we failed to accomplish the sex-specific, IBS subtype-specific, age-specific, and race-specific analyses due to a lack of data. Lastly, MR analysis possesses some inherent shortcomings, making it impossible to eliminate the effects of confounding factors and horizontal pleiotropy.
In conclusion, the present study provides no evidence that calcium, Vit-D, and PTH are causally associated with IBS, and it suggests a lower concentration of PTH in IBS subjects. Our findings may reduce possible expenses and research interests in elucidating the effects of calcium, Vit-D, and PTH on IBS. More importantly, further research is needed to investigate the causal relationship between micronutrients and IBS.
Appendix A
Table A1.
The F statistics for SNPs strongly associated with vitamin D.
| SNP | Eaf | Beta | R2 | F |
|---|---|---|---|---|
| rs10277163 | 0.255 | −0.014 | 0.0001 | 39 |
| rs1038165 | 0.579 | 0.012 | 0.0001 | 32 |
| rs1042034 | 0.792 | −0.015 | 0.0001 | 37 |
| rs10438978 | 0.820 | −0.017 | 0.0001 | 43 |
| rs1047891 | 0.317 | −0.013 | 0.0001 | 39 |
| rs1048328 | 0.080 | 0.031 | 0.0001 | 72 |
| rs10859995 | 0.580 | −0.044 | 0.0009 | 461 |
| rs11023159 | 0.033 | 0.048 | 0.0001 | 73 |
| rs11076175 | 0.176 | 0.023 | 0.0002 | 76 |
| rs111515741 | 0.017 | −0.049 | 0.0001 | 40 |
| rs11207969 | 0.351 | 0.021 | 0.0002 | 99 |
| rs11264361 | 0.251 | 0.017 | 0.0001 | 57 |
| rs11542462 | 0.134 | −0.025 | 0.0001 | 71 |
| rs11600054 | 0.010 | 0.068 | 0.0001 | 46 |
| rs11726886 | 0.291 | −0.054 | 0.0012 | 591 |
| rs117300835 | 0.013 | −0.335 | 0.0029 | 1469 |
| rs11791258 | 0.191 | 0.014 | 0.0001 | 30 |
| rs11867297 | 0.385 | 0.014 | 0.0001 | 43 |
| rs12056768 | 0.584 | −0.023 | 0.0003 | 130 |
| rs12283049 | 0.234 | −0.056 | 0.0011 | 569 |
| rs12324720 | 0.175 | −0.015 | 0.0001 | 32 |
| rs12462826 | 0.370 | −0.013 | 0.0001 | 40 |
| rs12501515 | 0.590 | −0.079 | 0.0030 | 1504 |
| rs12775091 | 0.213 | 0.016 | 0.0001 | 40 |
| rs1321247 | 0.102 | −0.022 | 0.0001 | 45 |
| rs13294734 | 0.466 | 0.013 | 0.0001 | 39 |
| rs138335 | 0.659 | −0.014 | 0.0001 | 42 |
| rs1384687 | 0.132 | −0.017 | 0.0001 | 32 |
| rs142004400 | 0.034 | −0.031 | 0.0001 | 32 |
| rs142158911 | 0.112 | 0.026 | 0.0001 | 68 |
| rs1532085 | 0.617 | 0.025 | 0.0003 | 150 |
| rs1627043 | 0.033 | −0.049 | 0.0002 | 76 |
| rs1684600 | 0.299 | −0.013 | 0.0001 | 33 |
| rs17207784 | 0.324 | −0.013 | 0.0001 | 40 |
| rs17473257 | 0.017 | −0.061 | 0.0001 | 63 |
| rs1800588 | 0.215 | −0.031 | 0.0003 | 156 |
| rs1858889 | 0.503 | 0.013 | 0.0001 | 45 |
| rs1871395 | 0.153 | −0.020 | 0.0001 | 53 |
| rs1949633 | 0.606 | 0.011 | 0.0001 | 31 |
| rs2037511 | 0.166 | 0.018 | 0.0001 | 43 |
| rs2074735 | 0.065 | 0.029 | 0.0001 | 52 |
| rs2229742 | 0.105 | −0.025 | 0.0001 | 58 |
| rs2245133 | 0.164 | −0.021 | 0.0001 | 62 |
| rs2297991 | 0.718 | 0.013 | 0.0001 | 33 |
| rs2494429 | 0.823 | −0.015 | 0.0001 | 32 |
| rs2511279 | 0.960 | 0.098 | 0.0007 | 365 |
| rs2595644 | 0.385 | −0.012 | 0.0001 | 35 |
| rs2710651 | 0.526 | −0.012 | 0.0001 | 33 |
| rs2807834 | 0.685 | −0.015 | 0.0001 | 49 |
| rs28435470 | 0.663 | −0.012 | 0.0001 | 31 |
| rs2847500 | 0.123 | −0.023 | 0.0001 | 55 |
| rs325393 | 0.278 | −0.014 | 0.0001 | 37 |
| rs34186890 | 0.260 | −0.016 | 0.0001 | 47 |
| rs34726834 | 0.252 | 0.014 | 0.0001 | 37 |
| rs35270497 | 0.176 | 0.016 | 0.0001 | 35 |
| rs3732220 | 0.085 | −0.048 | 0.0004 | 177 |
| rs3829251 | 0.133 | −0.114 | 0.0030 | 1508 |
| rs4147536 | 0.789 | −0.015 | 0.0001 | 36 |
| rs4348160 | 0.327 | −0.026 | 0.0003 | 146 |
| rs4364259 | 0.199 | 0.017 | 0.0001 | 47 |
| rs4420638 | 0.177 | −0.019 | 0.0001 | 54 |
| rs4580037 | 0.286 | −0.014 | 0.0001 | 37 |
| rs512083 | 0.462 | 0.012 | 0.0001 | 37 |
| rs5770794 | 0.314 | −0.013 | 0.0001 | 38 |
| rs6129648 | 0.380 | 0.014 | 0.0001 | 46 |
| rs61698755 | 0.560 | −0.011 | 0.0001 | 32 |
| rs61747728 | 0.039 | 0.030 | 0.0001 | 34 |
| rs61813875 | 0.025 | 0.082 | 0.0003 | 162 |
| rs61887421 | 0.030 | −0.037 | 0.0001 | 39 |
| rs62007299 | 0.713 | −0.012 | 0.0001 | 31 |
| rs62129966 | 0.161 | 0.061 | 0.0010 | 502 |
| rs635634 | 0.187 | −0.015 | 0.0001 | 34 |
| rs6438900 | 0.256 | 0.015 | 0.0001 | 43 |
| rs6672758 | 0.800 | 0.016 | 0.0001 | 42 |
| rs6834488 | 0.423 | −0.014 | 0.0001 | 51 |
| rs71599974 | 0.148 | 0.026 | 0.0002 | 83 |
| rs727857 | 0.612 | −0.012 | 0.0001 | 34 |
| rs733454 | 0.099 | 0.019 | 0.0001 | 32 |
| rs73413596 | 0.074 | 0.022 | 0.0001 | 34 |
| rs742493 | 0.113 | 0.018 | 0.0001 | 34 |
| rs7528419 | 0.224 | 0.022 | 0.0002 | 80 |
| rs7569755 | 0.289 | 0.014 | 0.0001 | 38 |
| rs7580771 | 0.176 | −0.017 | 0.0001 | 40 |
| rs7712001 | 0.440 | 0.012 | 0.0001 | 35 |
| rs77532868 | 0.052 | 0.026 | 0.0001 | 33 |
| rs77924615 | 0.194 | −0.015 | 0.0001 | 36 |
| rs77960347 | 0.013 | −0.053 | 0.0001 | 34 |
| rs78649910 | 0.106 | −0.019 | 0.0001 | 34 |
| rs8018720 | 0.824 | −0.034 | 0.0003 | 172 |
| rs8107974 | 0.076 | 0.036 | 0.0002 | 89 |
| rs8121940 | 0.198 | −0.044 | 0.0006 | 299 |
| rs9375037 | 0.443 | 0.012 | 0.0001 | 34 |
| rs9409266 | 0.862 | −0.017 | 0.0001 | 33 |
| rs964184 | 0.867 | 0.041 | 0.0004 | 189 |
| rs9847248 | 0.713 | −0.012 | 0.0001 | 31 |
| rs986649 | 0.322 | 0.013 | 0.0001 | 36 |
| rs9946771 | 0.066 | −0.023 | 0.0001 | 34 |
Table A2.
The F statistics for SNPs strongly associated with calcium.
| SNP | Eaf | Beta | R2 | F |
|---|---|---|---|---|
| rs10108887 | 0.388 | 0.014 | 0.0001 | 31 |
| rs1036332 | 0.739 | 0.022 | 0.0002 | 59 |
| rs1061134 | 0.092 | −0.025 | 0.0001 | 33 |
| rs10754439 | 0.417 | 0.014 | 0.0001 | 32 |
| rs10819178 | 0.638 | 0.032 | 0.0005 | 153 |
| rs10858935 | 0.687 | −0.019 | 0.0002 | 51 |
| rs10917386 | 0.690 | 0.020 | 0.0002 | 54 |
| rs10958700 | 0.247 | 0.020 | 0.0002 | 48 |
| rs11078597 | 0.186 | 0.051 | 0.0008 | 249 |
| rs11085015 | 0.800 | −0.018 | 0.0001 | 33 |
| rs112174050 | 0.025 | 0.102 | 0.0005 | 163 |
| rs114949263 | 0.112 | 0.034 | 0.0002 | 72 |
| rs11588907 | 0.342 | −0.016 | 0.0001 | 36 |
| rs11616030 | 0.087 | −0.031 | 0.0002 | 48 |
| rs11621792 | 0.454 | 0.016 | 0.0001 | 39 |
| rs11629876 | 0.331 | −0.018 | 0.0001 | 46 |
| rs11671393 | 0.040 | −0.045 | 0.0002 | 48 |
| rs116769926 | 0.024 | 0.073 | 0.0002 | 76 |
| rs117080418 | 0.011 | −0.099 | 0.0002 | 64 |
| rs117179023 | 0.012 | −0.068 | 0.0001 | 34 |
| rs117213754 | 0.015 | 0.104 | 0.0003 | 100 |
| rs11730491 | 0.168 | 0.021 | 0.0001 | 38 |
| rs11743466 | 0.364 | 0.018 | 0.0001 | 45 |
| rs117896857 | 0.027 | −0.055 | 0.0002 | 51 |
| rs11792928 | 0.295 | −0.017 | 0.0001 | 36 |
| rs12132412 | 0.388 | 0.028 | 0.0004 | 121 |
| rs12135382 | 0.584 | 0.022 | 0.0002 | 76 |
| rs12147703 | 0.895 | −0.028 | 0.0001 | 47 |
| rs12339541 | 0.064 | −0.061 | 0.0004 | 141 |
| rs12378991 | 0.080 | −0.038 | 0.0002 | 67 |
| rs12583851 | 0.751 | −0.023 | 0.0002 | 60 |
| rs12613807 | 0.444 | 0.016 | 0.0001 | 40 |
| rs12675477 | 0.274 | 0.017 | 0.0001 | 37 |
| rs12793731 | 0.511 | 0.015 | 0.0001 | 34 |
| rs12918968 | 0.439 | −0.032 | 0.0005 | 157 |
| rs12922549 | 0.237 | −0.022 | 0.0002 | 55 |
| rs12933858 | 0.493 | 0.019 | 0.0002 | 56 |
| rs12982234 | 0.040 | −0.058 | 0.0003 | 82 |
| rs12998379 | 0.194 | −0.024 | 0.0002 | 58 |
| rs13073106 | 0.641 | 0.038 | 0.0007 | 205 |
| rs13389219 | 0.394 | −0.016 | 0.0001 | 40 |
| rs1354034 | 0.601 | −0.018 | 0.0002 | 49 |
| rs1374161 | 0.491 | −0.023 | 0.0003 | 80 |
| rs138789759 | 0.075 | 0.047 | 0.0003 | 96 |
| rs147233090 | 0.024 | 0.103 | 0.0005 | 157 |
| rs1476698 | 0.369 | −0.021 | 0.0002 | 62 |
| rs1497826 | 0.373 | 0.024 | 0.0003 | 86 |
| rs149807892 | 0.016 | 0.066 | 0.0001 | 43 |
| rs1500187 | 0.456 | −0.014 | 0.0001 | 29 |
| rs164751 | 0.410 | −0.019 | 0.0002 | 54 |
| rs165316 | 0.198 | −0.018 | 0.0001 | 31 |
| rs1672991 | 0.934 | 0.075 | 0.0007 | 221 |
| rs17132144 | 0.093 | −0.026 | 0.0001 | 35 |
| rs17164683 | 0.270 | −0.021 | 0.0002 | 55 |
| rs17580 | 0.049 | 0.047 | 0.0002 | 64 |
| rs1763519 | 0.607 | −0.032 | 0.0005 | 149 |
| rs17774672 | 0.158 | −0.027 | 0.0002 | 62 |
| rs17884869 | 0.025 | −0.111 | 0.0006 | 190 |
| rs1801282 | 0.120 | −0.037 | 0.0003 | 92 |
| rs1858800 | 0.345 | 0.031 | 0.0004 | 134 |
| rs2001884 | 0.507 | −0.017 | 0.0001 | 46 |
| rs2004315 | 0.625 | 0.033 | 0.0005 | 160 |
| rs2241699 | 0.277 | −0.026 | 0.0003 | 84 |
| rs2243010 | 0.206 | −0.018 | 0.0001 | 32 |
| rs2249825 | 0.269 | −0.016 | 0.0001 | 33 |
| rs2274224 | 0.432 | −0.017 | 0.0001 | 47 |
| rs2309233 | 0.731 | 0.021 | 0.0002 | 56 |
| rs2327774 | 0.378 | −0.022 | 0.0002 | 71 |
| rs2335534 | 0.179 | −0.038 | 0.0004 | 136 |
| rs2343592 | 0.267 | −0.023 | 0.0002 | 67 |
| rs2370218 | 0.766 | −0.022 | 0.0002 | 53 |
| rs2419886 | 0.257 | −0.020 | 0.0001 | 47 |
| rs255755 | 0.270 | 0.015 | 0.0001 | 29 |
| rs2647242 | 0.798 | −0.020 | 0.0001 | 40 |
| rs2762938 | 0.587 | 0.016 | 0.0001 | 37 |
| rs28520334 | 0.119 | 0.022 | 0.0001 | 31 |
| rs28929474 | 0.020 | 0.123 | 0.0006 | 189 |
| rs2971855 | 0.302 | 0.019 | 0.0002 | 49 |
| rs3011642 | 0.243 | 0.020 | 0.0001 | 45 |
| rs3026445 | 0.367 | −0.018 | 0.0001 | 45 |
| rs302650 | 0.432 | −0.019 | 0.0002 | 58 |
| rs3091842 | 0.044 | 0.094 | 0.0007 | 235 |
| rs3133548 | 0.142 | 0.020 | 0.0001 | 31 |
| rs34042070 | 0.186 | 0.021 | 0.0001 | 42 |
| rs34066945 | 0.358 | −0.026 | 0.0003 | 97 |
| rs34290411 | 0.286 | 0.018 | 0.0001 | 41 |
| rs34395935 | 0.152 | 0.059 | 0.0009 | 285 |
| rs35118755 | 0.149 | 0.023 | 0.0001 | 43 |
| rs35590487 | 0.241 | −0.021 | 0.0002 | 53 |
| rs35751693 | 0.039 | 0.043 | 0.0001 | 45 |
| rs35852840 | 0.059 | 0.029 | 0.0001 | 29 |
| rs36086195 | 0.580 | 0.020 | 0.0002 | 63 |
| rs36104352 | 0.121 | 0.028 | 0.0002 | 52 |
| rs3748861 | 0.202 | −0.017 | 0.0001 | 31 |
| rs3795243 | 0.126 | 0.022 | 0.0001 | 32 |
| rs3822858 | 0.407 | −0.016 | 0.0001 | 40 |
| rs3931841 | 0.681 | −0.026 | 0.0003 | 94 |
| rs4082330 | 0.814 | 0.021 | 0.0001 | 41 |
| rs41278174 | 0.027 | 0.050 | 0.0001 | 42 |
| rs41393948 | 0.113 | −0.022 | 0.0001 | 29 |
| rs4239142 | 0.745 | −0.017 | 0.0001 | 35 |
| rs4320103 | 0.039 | 0.045 | 0.0002 | 49 |
| rs4324076 | 0.530 | −0.018 | 0.0002 | 53 |
| rs4633480 | 0.556 | 0.020 | 0.0002 | 62 |
| rs4721467 | 0.738 | −0.021 | 0.0002 | 54 |
| rs4744854 | 0.629 | −0.033 | 0.0005 | 156 |
| rs4758621 | 0.308 | −0.026 | 0.0003 | 94 |
| rs4790310 | 0.575 | −0.020 | 0.0002 | 59 |
| rs4841132 | 0.908 | 0.057 | 0.0005 | 171 |
| rs4938642 | 0.074 | 0.034 | 0.0002 | 49 |
| rs4976647 | 0.332 | 0.018 | 0.0001 | 47 |
| rs498490 | 0.164 | −0.031 | 0.0003 | 82 |
| rs55772024 | 0.242 | −0.017 | 0.0001 | 32 |
| rs56406311 | 0.386 | 0.018 | 0.0002 | 47 |
| rs567743 | 0.708 | 0.015 | 0.0001 | 29 |
| rs5751350 | 0.330 | 0.016 | 0.0001 | 37 |
| rs5760495 | 0.354 | 0.017 | 0.0001 | 41 |
| rs5786388 | 0.581 | 0.022 | 0.0002 | 71 |
| rs58579887 | 0.404 | 0.016 | 0.0001 | 40 |
| rs59821684 | 0.029 | 0.054 | 0.0002 | 52 |
| rs6127099 | 0.278 | −0.053 | 0.0011 | 358 |
| rs62134679 | 0.148 | 0.022 | 0.0001 | 39 |
| rs62211622 | 0.184 | −0.018 | 0.0001 | 32 |
| rs62309863 | 0.586 | −0.014 | 0.0001 | 32 |
| rs62472728 | 0.060 | 0.032 | 0.0001 | 36 |
| rs634916 | 0.511 | −0.014 | 0.0001 | 31 |
| rs648514 | 0.467 | −0.014 | 0.0001 | 30 |
| rs6580981 | 0.458 | −0.018 | 0.0002 | 52 |
| rs66920316 | 0.196 | −0.021 | 0.0001 | 45 |
| rs6741561 | 0.393 | −0.038 | 0.0007 | 222 |
| rs6771438 | 0.116 | −0.027 | 0.0002 | 48 |
| rs6841429 | 0.166 | −0.040 | 0.0004 | 137 |
| rs6909201 | 0.517 | −0.042 | 0.0009 | 281 |
| rs710217 | 0.485 | 0.024 | 0.0003 | 94 |
| rs71565393 | 0.177 | 0.018 | 0.0001 | 30 |
| rs7221118 | 0.215 | −0.020 | 0.0001 | 41 |
| rs722298 | 0.438 | 0.015 | 0.0001 | 34 |
| rs72660383 | 0.064 | −0.028 | 0.0001 | 30 |
| rs72697816 | 0.163 | 0.020 | 0.0001 | 33 |
| rs73001065 | 0.071 | 0.036 | 0.0002 | 53 |
| rs73186030 | 0.128 | 0.193 | 0.0083 | 2637 |
| rs73186098 | 0.015 | −0.091 | 0.0002 | 78 |
| rs73536752 | 0.043 | −0.033 | 0.0001 | 29 |
| rs7370877 | 0.420 | −0.017 | 0.0001 | 44 |
| rs7402977 | 0.267 | −0.016 | 0.0001 | 30 |
| rs74230087 | 0.078 | −0.055 | 0.0004 | 134 |
| rs7533348 | 0.352 | −0.021 | 0.0002 | 61 |
| rs7546838 | 0.651 | 0.020 | 0.0002 | 55 |
| rs7559013 | 0.130 | 0.025 | 0.0001 | 46 |
| rs75702986 | 0.188 | 0.037 | 0.0004 | 134 |
| rs7587636 | 0.529 | −0.016 | 0.0001 | 38 |
| rs75895430 | 0.033 | 0.080 | 0.0004 | 126 |
| rs7592216 | 0.869 | −0.020 | 0.0001 | 30 |
| rs7599 | 0.634 | −0.019 | 0.0002 | 55 |
| rs7688574 | 0.369 | 0.015 | 0.0001 | 32 |
| rs7730344 | 0.293 | 0.017 | 0.0001 | 40 |
| rs77542162 | 0.023 | −0.089 | 0.0004 | 113 |
| rs777588 | 0.578 | −0.029 | 0.0004 | 126 |
| rs778368 | 0.585 | −0.014 | 0.0001 | 30 |
| rs7786368 | 0.416 | −0.024 | 0.0003 | 90 |
| rs7864156 | 0.390 | 0.019 | 0.0002 | 55 |
| rs7913072 | 0.859 | −0.021 | 0.0001 | 33 |
| rs7924737 | 0.349 | −0.015 | 0.0001 | 34 |
| rs7940215 | 0.434 | 0.014 | 0.0001 | 30 |
| rs79501693 | 0.021 | −0.050 | 0.0001 | 32 |
| rs8041057 | 0.714 | −0.015 | 0.0001 | 30 |
| rs835664 | 0.456 | −0.017 | 0.0001 | 46 |
| rs838717 | 0.566 | −0.046 | 0.0010 | 327 |
| rs883951 | 0.261 | 0.023 | 0.0002 | 66 |
| rs928760 | 0.303 | −0.018 | 0.0001 | 45 |
| rs9388399 | 0.312 | −0.024 | 0.0003 | 81 |
| rs9399697 | 0.464 | 0.014 | 0.0001 | 32 |
| rs9419741 | 0.479 | 0.015 | 0.0001 | 36 |
| rs945890 | 0.714 | −0.017 | 0.0001 | 37 |
| rs949300 | 0.380 | 0.015 | 0.0001 | 35 |
| rs9530 | 0.549 | −0.031 | 0.0005 | 149 |
| rs9532958 | 0.855 | 0.035 | 0.0003 | 99 |
| rs9611396 | 0.655 | −0.014 | 0.0001 | 29 |
| rs9895661 | 0.831 | −0.028 | 0.0002 | 69 |
Table A3.
The F statistics for SNPs strongly associated with parathyroid hormone.
| SNP | Eaf | Beta | R2 | F |
|---|---|---|---|---|
| rs10886704 | 0.425 | 0.121 | 0.007 | 24 |
| rs10902764 | 0.576 | 0.131 | 0.008 | 28 |
| rs150350229 | 0.026 | −0.388 | 0.008 | 25 |
| rs16895559 | 0.043 | 0.286 | 0.007 | 22 |
| rs17267730 | 0.045 | 0.292 | 0.007 | 24 |
| rs2585442 | 0.249 | −0.158 | 0.009 | 31 |
| rs34421071 | 0.171 | −0.155 | 0.007 | 23 |
| rs464202 | 0.888 | −0.181 | 0.007 | 22 |
| rs62533188 | 0.106 | −0.191 | 0.007 | 23 |
| rs678360 | 0.962 | −0.346 | 0.009 | 29 |
| rs73556612 | 0.035 | 0.328 | 0.007 | 24 |
| rs7514637 | 0.788 | −0.148 | 0.007 | 24 |
| rs753409 | 0.201 | 0.151 | 0.007 | 24 |
| rs9316680 | 0.384 | −0.137 | 0.009 | 30 |
| rs950455 | 0.317 | 0.129 | 0.007 | 24 |
Table A4.
The F statistics for SNPs strongly associated with irritable bowel syndrome.
| SNP | Eaf | Beta | R2 | F |
|---|---|---|---|---|
| rs10275986 | 0.316 | −0.113 | 0.005 | 1028 |
| rs10985554 | 0.394 | 0.103 | 0.005 | 947 |
| rs11952072 | 0.113 | 0.157 | 0.005 | 932 |
| rs12570677 | 0.112 | −0.158 | 0.005 | 935 |
| rs12956689 | 0.400 | −0.102 | 0.005 | 930 |
| rs147367149 | 0.010 | −0.521 | 0.006 | 1042 |
| rs177503 | 0.358 | −0.105 | 0.005 | 951 |
| rs45506200 | 0.015 | 0.416 | 0.005 | 957 |
| rs735820 | 0.001 | 2.070 | 0.009 | 1623 |
| rs763614 | 0.329 | 0.107 | 0.005 | 948 |
Author Contributions
N.X., N.L., F.X. and J.W. (Jian Wu) conceptualized and designed the study; Z.W. and J.X. analyzed the data; Q.S. interpreted the data; N.X. wrote the original draft; H.S. and J.W. (Jinhai Wang) commented on and improved the manuscript; N.L., F.X. and J.W. (Jian Wu) reviewed the manuscript, obtained the funding, and supervised all research work. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Ethical approval and consent to participate were not needed for this current study because it is a secondary analysis of previously published data. In all original studies related to this study, ethical approval and consent to participate were obtained.
Data Availability Statement
This study is based on the public database, and all related-datasets are available at https://gwas.mrcieu.ac.uk/ (accessed on 10 October 2022).
Conflicts of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Funding Statement
The study was supported by grants from the National Natural Science Foundation of China (No. 81872397) and National Key Technology R&D Program of China (No. 2015BAI13B07).
Footnotes
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Ford A.C., Sperber A.D., Corsetti M., Camilleri M. Irritable bowel syndrome. Lancet. 2020;396:1675–1688. doi: 10.1016/S0140-6736(20)31548-8. [DOI] [PubMed] [Google Scholar]
- 2.Camilleri M. Diagnosis and Treatment of Irritable Bowel Syndrome: A Review. JAMA. 2021;325:865–877. doi: 10.1001/jama.2020.22532. [DOI] [PubMed] [Google Scholar]
- 3.Black C., Ford A. Global burden of irritable bowel syndrome: Trends, predictions and risk factors. Nat. Rev. Gastroenterol. Hepatol. 2020;17:473–486. doi: 10.1038/s41575-020-0286-8. [DOI] [PubMed] [Google Scholar]
- 4.Camilleri M., Zhernakova A., Bozzarelli I., D’Amato M. Genetics of irritable bowel syndrome: Shifting gear via biobank-scale studies. Nat. Rev. Gastroenterol. Hepatol. 2022;19:689–702. doi: 10.1038/s41575-022-00662-2. [DOI] [PubMed] [Google Scholar]
- 5.Liu Y.L., Liu J.S. Irritable bowel syndrome in China: A review on the epidemiology, diagnosis, and management. Chin. Med. J. 2021;134:1396–1401. doi: 10.1097/CM9.0000000000001550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Böhn L., Störsrud S., Törnblom H., Bengtsson U., Simrén M. Self-reported food-related gastrointestinal symptoms in IBS are common and associated with more severe symptoms and reduced quality of life. Am. J. Gastroenterol. 2013;108:634–641. doi: 10.1038/ajg.2013.105. [DOI] [PubMed] [Google Scholar]
- 7.Bek S., Teo Y.N., Tan X.H., Fan K.H.R., Siah K.T.H. Association between irritable bowel syndrome and micronutrients: A systematic review. J. Gastroenterol. Hepatol. 2022;37:1485–1497. doi: 10.1111/jgh.15891. [DOI] [PubMed] [Google Scholar]
- 8.Gill S., Rossi M., Bajka B., Whelan K. Dietary fibre in gastrointestinal health and disease. Nat. Rev. Gastroenterol. Hepatol. 2021;18:101–116. doi: 10.1038/s41575-020-00375-4. [DOI] [PubMed] [Google Scholar]
- 9.Müller M., Canfora E.E., Blaak E.E. Gastrointestinal Transit Time, Glucose Homeostasis and Metabolic Health: Modulation by Dietary Fibers. Nutrients. 2018;10:275. doi: 10.3390/nu10030275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bijkerk C.J., de Wit N.J., Muris J.W., Whorwell P.J., Knottnerus J.A., Hoes A.W. Soluble or insoluble fibre in irritable bowel syndrome in primary care? Randomised placebo controlled trial. BMJ. 2009;339:b3154. doi: 10.1136/bmj.b3154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Black C.J., Staudacher H.M., Ford A.C. Efficacy of a low FODMAP diet in irritable bowel syndrome: Systematic review and network meta-analysis. Gut. 2022;71:1117–1126. doi: 10.1136/gutjnl-2021-325214. [DOI] [PubMed] [Google Scholar]
- 12.Matikainen N., Pekkarinen T., Ryhänen E.M., Schalin-Jäntti C. Physiology of Calcium Homeostasis: An Overview. Endocrinol. Metab. Clin. N. Am. 2021;50:575–590. doi: 10.1016/j.ecl.2021.07.005. [DOI] [PubMed] [Google Scholar]
- 13.Glabska D., Kolota A., Lachowicz K., Skolmowska D., Stachon M., Guzek D. Vitamin D Supplementation and Mental Health in Inflammatory Bowel Diseases and Irritable Bowel Syndrome Patients: A Systematic Review. Nutrients. 2021;13:3662. doi: 10.3390/nu13103662. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jalili M., Vahedi H., Poustchi H., Hekmatdoost A. Effects of Vitamin D Supplementation in Patients with Irritable Bowel Syndrome: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial. Int. J. Prev. Med. 2019;10:16. doi: 10.4103/ijpvm.IJPVM_512_17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Williams C.E., Williams E.A., Corfe B.M. Vitamin D supplementation in people with IBS has no effect on symptom severity and quality of life: Results of a randomised controlled trial. Eur. J. Nutr. 2022;61:299–308. doi: 10.1007/s00394-021-02633-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Abboud M., Haidar S., Mahboub N., Papandreou D., Al Anouti F., Rizk R. Association between Serum Vitamin D and Irritable Bowel Syndrome Symptoms in a Sample of Adults. Nutrients. 2022;14:4157. doi: 10.3390/nu14194157. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Emdin C.A., Khera A.V., Kathiresan S. Mendelian Randomization. JAMA. 2017;318:1925–1926. doi: 10.1001/jama.2017.17219. [DOI] [PubMed] [Google Scholar]
- 18.Revez J.A., Lin T., Qiao Z., Xue A., Holtz Y., Zhu Z., Zeng J., Wang H., Sidorenko J., Kemper K.E., et al. Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration. Nat. Commun. 2020;11:1647. doi: 10.1038/s41467-020-15421-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Sun B.B., Maranville J.C., Peters J.E., Stacey D., Staley J.R., Blackshaw J., Burgess S., Jiang T., Paige E., Surendran P., et al. Genomic atlas of the human plasma proteome. Nature. 2018;558:73–79. doi: 10.1038/s41586-018-0175-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kurki M.I., Karjalainen J., Palta P., Sipilä T.P., Kristiansson K., Donner K., Reeve M.P., Laivuori H., Aavikko M., Kaunisto M.A., et al. FinnGen: Unique genetic insights from combining isolated population and national health register data. medRxiv. 2022 [Google Scholar]
- 21.Kamat M.A., Blackshaw J.A., Young R., Surendran P., Burgess S., Danesh J., Butterworth A.S., Staley J.R. PhenoScanner V2: An expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35:4851–4853. doi: 10.1093/bioinformatics/btz469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Reding K.W., Cain K.C., Jarrett M.E., Eugenio M.D., Heitkemper M.M. Relationship between patterns of alcohol consumption and gastrointestinal symptoms among patients with irritable bowel syndrome. Am. J. Gastroenterol. 2013;108:270–276. doi: 10.1038/ajg.2012.414. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Talley N.J., Powell N., Walker M.M., Jones M.P., Ronkainen J., Forsberg A., Kjellstrom L., Hellstrom P.M., Aro P., Wallner B., et al. Role of smoking in functional dyspepsia and irritable bowel syndrome: Three random population-based studies. Aliment Pharm. Ther. 2021;54:32–42. doi: 10.1111/apt.16372. [DOI] [PubMed] [Google Scholar]
- 24.Creed F. Review article: The incidence and risk factors for irritable bowel syndrome in population-based studies. Aliment Pharm. Ther. 2019;50:507–516. doi: 10.1111/apt.15396. [DOI] [PubMed] [Google Scholar]
- 25.Palmer T.M., Lawlor D.A., Harbord R.M., Sheehan N.A., Tobias J.H., Timpson N.J., Davey Smith G., Sterne J.A. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat. Methods Med. Res. 2012;21:223–242. doi: 10.1177/0962280210394459. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Liu B., Ye D., Yang H., Song J., Sun X., Mao Y., He Z. Two-Sample Mendelian Randomization Analysis Investigates Causal Associations Between Gut Microbial Genera and Inflammatory Bowel Disease, and Specificity Causal Associations in Ulcerative Colitis or Crohn’s Disease. Front. Immunol. 2022;13:921546. doi: 10.3389/fimmu.2022.921546. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Pham V.T., Fehlbaum S., Seifert N., Richard N., Bruins M.J., Sybesma W., Rehman A., Steinert R.E. Effects of colon-targeted vitamins on the composition and metabolic activity of the human gut microbiome—A pilot study. Gut Microbes. 2021;13:1–20. doi: 10.1080/19490976.2021.1875774. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Peacock M. Calcium metabolism in health and disease. Clin. J. Am. Soc. Nephrol. 2010;5((Suppl. S1)):S23–S30. doi: 10.2215/CJN.05910809. [DOI] [PubMed] [Google Scholar]
- 29.Na S.Y., Kim K.B., Lim Y.J., Song H.J. Vitamin D and Colorectal Cancer: Current Perspectives and Future Directions. J. Cancer Prev. 2022;27:147–156. doi: 10.15430/JCP.2022.27.3.147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Huang H., Lu L., Chen Y., Zeng Y., Xu C. The efficacy of vitamin D supplementation for irritable bowel syndrome: A systematic review with meta-analysis. Nutr. J. 2022;21:24. doi: 10.1186/s12937-022-00777-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Abuelazm M., Muhammad S., Gamal M., Labieb F., Amin M.A., Abdelazeem B., Brasic J.R. The Effect of Vitamin D Supplementation on the Severity of Symptoms and the Quality of Life in Irritable Bowel Syndrome Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2022;14:2618. doi: 10.3390/nu14132618. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Wongtrakul W., Charoenngam N., Ungprasert P. The association between irritable bowel syndrome and osteoporosis: A systematic review and meta-analysis. Osteoporos. Int. 2020;31:1049–1057. doi: 10.1007/s00198-020-05318-y. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
This study is based on the public database, and all related-datasets are available at https://gwas.mrcieu.ac.uk/ (accessed on 10 October 2022).